It occurs when you irrationally cling to things that had already cost you something.

We often continue working on a project simply because we have already put time into it, even if it isn’t the most impactful thing that we could be doing.

It’s not hard to realize this.

You probably already have a gut feeling if it’s happening.

The tricky part is making the call.

Quitting a project and moving on is a tough pill to swallow.

While other biases on this list are definitely sneakier, sunk cost fallacy might be the most difficult to deal with head-on.

Advice: As difficult as it is, focus on future results.

The past is the past.

It can’t be changed and shouldn’t be driving your decision.

As the project stands right now, is it the best time investment towards future results?.If the answer is no, think long and hard about continuing the journey.

Curse of KnowledgeCommunication isn’t easy.

It’s even less easy when the curse of knowledge gets ahold of us.

The curse of knowledge is when you know something, and presume it’s obvious to everyone.

For data scientists, this can be a serious Achilles’ heel.

We are technical by nature.

We do lots of analysis.

We dig into lots of hypotheses.

Slowly, we use data to build up a picture of what’s really going on behind the scenes.

Where this often goes wrong, is when we share these insights.

We fail to remember that others haven’t done the due diligence that we have.

They haven’t developed the same understanding of the problem.

They haven’t dug into all of the hypotheses.

So when we communicate results, they come off as difficult to interpret or overly complex.

Advice: Put yourself in the shoes of your stakeholders.

Does this make sense to someone that doesn’t have as deep of an understanding of the problem?.Is my presentation or document overly complex?.Communicate as clearly and concisely as possible.

Focus on actionable insights first, then go deeper if need be.

Information BiasAs data scientists, we crave information.

It’s at the core of what we do.

Our attention to detail here is both one of our greatest assets and pitfalls.

If you aren’t familiar, information bias is the tendency to continue to seek out information when it doesn’t affect action.

Analysis paralysis is an unavoidable plague.

At a certain point, even though it’s important to explore, the diminishing gains of looking further into a problem aren’t going to directly affect the greater outcome of the project.

In these cases, your time is best spent elsewhere.

Advice: Start with the minimum viable analysis.

Do as little as possible to get a baseline of information and understanding.

Present that to your stakeholder and get their feedback.

Surprisingly often, it will be enough.

SummaryThere’s something both discomforting and fascinating about the realization that we aren’t quite as in control of our decisions and thinking as we think.

With the depth of accessible information in the world, clear and relatively unbiased thinking has turned into an often overlooked superpower.

Throughout this post, I laid out some practices that I’ve found helpful.

These can roughly be broken down into the following points:Write things down beforehandTalk to others with diverse perspectivesAsk yourself hard questionsPut yourself in the shoes of stakeholdersThese four things will take you a long way.

Writing things down beforehand will keep you honest.

Talking to others will help you check your cognitive blindspots.

Hard questions will make you face hard decisions head-on.

Empathy for stakeholders will help you produce more meaningful work.

Cognitive biases are unavoidable, but this doesn’t mean we have to sit idly while they take the wheel.

With the right systems in place, we can take steps to tame them.

Go forth and conquer.

Thanks for reading!.Feel free to check out some of my similar essays below and subscribe to my newsletter for interesting links and new content.

Compilation of Advice for New and Aspiring Data ScientistsData Scientists Are Thinkers13 Essential Newsletters for Data ScientistsYou can follow me on Medium for more posts like this and find me on Twitter as well.